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A Methodology for the Disaggregate, Multidimensional Measurement of Residential Neighbourhood Type

South Texas Community College, PO Box 9701, McAllen, Texas 78502 9701, USA, mnbagley{at}stcc.cc.tx.us

Patricia L. Mokhtarian

Institute of Transport Studies, University of Cakfornia, Davis, California 95616, USA, plmokhtarian{at}ucdavis.edu

Ryuichi Kitamura

Department of Transport Engineering, Kyoto University, Sakyo-ku, Kyoto 606, Japan, rkitamura{at}term.kuciv.kyoto-u.ac.jp

Binary designation of a residential neighbourhood as either traditional or suburban is a distortion of reality, since a location may have some characteristics of both types and since residents in different parts of the neighbourhood may perceive its character differently. This paper presents and applies a methodology for assessing neighbourhood type that results in a measure that is continuous rather than binary, disaggregate rather than aggregate, and potentially multidimensional. Specifically, 18 variables identified by the literature as distinguishing traditional and suburban locations are measured for 852 residents of 5 San Francisco area neighbourhoods. These data are factor-analysed to develop scales on which each individual has a person-specific score. Although we expected a single 'traditionalness' dimension to result, instead we found two factors: traditional and suburban. Study neighbourhoods could and did score highly on both dimensions, and considerable individual variation within neighbourhood was observed. By more accurately capturing the complexity in classifying a neighbourhood and the heterogeneity of individual perception within a neighbourhood, use of this methodology to measure neighbourhood type is expected to improve models involving residential location as an endogenous or exogenous variable.

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